Early Detection of Sporadic Pancreatic Cancer: Summative Review
Open accessAbstract
Pancreatic cancer (PC) is estimated to become the second leading cause of cancer death in the United States by 2020. Early detection is the key to improving survival in PC. Addressing this urgent need, the Kenner Family Research Fund conducted the inaugural Early Detection of Sporadic Pancreatic Cancer Summit Conference in 2014 in conjunction with the 45th Anniversary Meeting of the American Pancreatic Association and Japan Pancreas Society. This seminal convening of international representatives from science, practice, and clinical research was designed to facilitate challenging interdisciplinary conversations to generate innovative ideas leading to the creation of a defined collaborative strategic pathway for the future of the field. An in-depth summary of current efforts in the field, analysis of gaps in specific areas of expertise, and challenges that exist in early detection is presented within distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. In addition, an overview of efforts in familial PC is presented in an addendum to this article. It is clear from the summit deliberations that only strategically designed collaboration among investigators, institutions, and funders will lead to significant progress in early detection of sporadic PC.
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If the stage distribution could be reversed to 50% localized and 10% metastatic, survival would be more than doubled without any additional improvements in therapy.
“If the stage distribution could be reversed, to 50% localized and 10% metastatic, survival would be more than doubled without any additional improvements in therapy.3”
From Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review (2021) · cites this paper as [3]
In “Survival in Pancreatic Cancer” (page unavailable), the paper models stage distributions that could double average 5-year survival using 2004–2010 SEER outcomes. Our copy does not give the table’s numerical distributions, so it cannot verify the specific 50% localized and 10% metastatic scenario or that survival would be more than doubled. The model uses outcomes under interventions available in 2004–2010, rather than assuming an additional treatment improvement. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe currently used blood-based biomarker, CA 19-9, accurately predicts only 65% of those with early disease when surgical treatment is a viable option.
“and the currently used blood-based biomarker, CA 19-9, accurately predicts only 65% of those with early disease when surgical treatment is a viable option.3,167”
From Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review (2021) · cites this paper as [3]
The Biomarkers for Early Detection overview identifies CA-19-9 as the only test in routine clinical use, but says it is used for therapeutic management, not diagnosis. The “Early PC Lacks Biomarkers” section reports 80.3% sensitivity across pancreatic-cancer patients and controls; it does not establish the claimed 65% figure for early, surgically treatable disease. Page numbers were not available in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measuredScreening in the asymptomatic population is not recommended due to the economic burden and the relatively low incidence of PC in the general population.
“However, screening in the asymptomatic population is not recommended due to the economic burden and the relatively low incidence of PC in the general population 21,22.”
From Artificial intelligence in pancreatic cancer (2022) · cites this paper as [22]
Early symptoms of PDAC are mostly nonspecific.
“Early symptoms of the disease are mostly nonspecific.”
From Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review (2021) · cites this paper as [2]
The size of the lesion at the time of surgery is a predictor of long-term survival.
“Furthermore, the size of the lesion at the time of surgery is a predictor of long-term survival.3,166,167”
From Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review (2021) · cites this paper as [3]
Several studies have shown that early detection of PDAC improves outcome.
“Several studies have shown that early detection of PDAC improves outcome.”
From Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review (2021) · cites this paper as [3]
Surgery is the only therapy to date associated with a durable long-term outcome.
“This result is based on the findings that surgery is the only therapy to date associated with a durable long-term outcome.”
From Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review (2021) · cites this paper as [3]
Many circulating tumor-derived analytes (proteins, autoantibodies, metabolites, DNA, non-coding RNAs, extracellular vesicles) have been assessed for PDAC early detection.
“a multitude of circulating tumor-derived analytes (proteins, autoantibodies, metabolites, DNA, non-coding RNAs and extracellular vesicles, among others) have been assessed in the context of PDAC early detection39–41.”
From Pancreatic cancer: Advances and challenges (2023) · cites this paper as [39]
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- Authors
- Chari, S. T., Kelly, K., Hollingsworth, M. A., Thayer, S. P., Ahlquist, D. A., Andersen, D. K., Batra, S. K., Brentnall, T. A., Canto, M., Cleeter, D. F., Firpo, M. A., Gambhir, S. S., Go, V. L. W., Hines, O. J., Kenner, B. J., Klimstra, D. S., Lerch, M. M., Levy, M. J., Maitra, A., Mulvihill, S. J., Petersen, G. M., Rhim, A. D., Simeone, D. M., Srivastava, S., Tanaka, M., Vinik, A. I., & Wong, D.
- Affiliations
- Mayo Clinic (US)
- Eastern Virginia Medical School (US)
- University of California, Los Angeles (US)
- National Institutes of Health (US)
- The University of Texas MD Anderson Cancer Center (US)
- University of Washington (US)
- Corresponding author
- Chari, Suresh T.
- Ahlquist, David A.
- Canto, Marcia
- Klimstra, David S.
- Tanaka, Masao
- ORCID
- Chari, Suresh T.
- Hollingsworth, Michael A.
- Thayer, Sarah P.
- Ahlquist, David A.
- Andersen, Dana K.
- Batra, Surinder K.
- Brentnall, Teresa A.
- Canto, Marcia
- Firpo, Matthew A.
- Gambhir, Sanjiv Sam
- Hines, O. Joe
- Kenner, Barbara J.
- Klimstra, David S.
- Lerch, Markus M.
- Levy, Michael J.
- Maitra, Anirban
- Mulvihill, Sean J.
- Petersen, Gloria M.
- Rhim, Andrew D.
- Simeone, Diane M.
- Srivastava, Sudhir
- Tanaka, Masao
- Vinik, Aaron I.
- Venue
- Pancreas
- Published
- 2015-07
- Volume
- 44
- Issue
- 5
- Pages
- 693-712
- ISSN
- 0885-3177 (ISSN-L)
- PMC
- PMC4467589
- OpenAlex
- W2064141899
- Cited by
- 295
- References
- 0
- Citations by year
- 2026: 13 · 2025: 10 · 2024: 24 · 2023: 20 · 2022: 34 · 2021: 35 · 2020: 28 · 2019: 30 · 2018: 30 · 2017: 31 · 2016: 30 · 2015: 8 · 2014: 2
- FWCI
- 14.41
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Pancreas (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Cancer Institute (P50CA102701, R01CA168712, R01CA177857)
- Topics
- Health Sciences › Medicine › Oncology › Pancreatic and Hepatic Oncology Research
- Health Sciences › Medicine › Surgery › Pancreatitis Pathology and Treatment
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Keywords
- pancreatic cancer, early detection, biomarkers, pancreatic imaging, familial pancreatic cancer, cancer survival, interdisciplinary collaboration, research gaps
- MeSH terms
- Biopsy, Congresses as Topic, Cooperative Behavior, Diagnostic Imaging, Diffusion of Innovation, Humans, International Cooperation, Pancreatic Neoplasms, Predictive Value of Tests, Prognosis, Biomarkers, Tumor, Survival Analysis, Carcinoma, Pancreatic Ductal, Molecular Diagnostic Techniques, Interdisciplinary Communication, Biomedical Research, Early Detection of Cancer
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